The following description is provided to assist the understanding of the reader. None of the information provided is admitted to be prior art.
In data storage architectures, a client's data may be stored in a volume. Typically, the volume's data resides on a small percentage of drives in a storage cluster. This arrangement leads to issues of hot spots where portions of the cluster are over-utilized while other portions of the cluster are under-utilized. For example, if a client is performing a large number of accesses of data in the volume, the load attributed to the small percentage of drives in which the data is stored increases, resulting in a hot spot. This arrangement may result in a client experience that is inconsistent across all volumes of the cluster as some clients may experience good performance if their data is stored on portions that are under-utilized and some clients experience poor performance if their data is stored on over-utilized portions.
One way of attempting to provide a better client experience is using quality of service based on client prioritization. For example, clients may be assigned different priority levels. Based on these priority levels, access requests (e.g., read and write requests) for various clients are prioritized. Clients' access requests are dispatched based on the load of the cluster and a priority assigned to each client. For example, a client having a higher priority may have more access requests processed than another client having a lower priority during times when the cluster is experiencing higher load. Using the priority system only allows for a slightly better client experience. For example, priorities do not guarantee a specific, consistent level of performance and are based on the idea that the cluster is dividing its full performance among all clients all the time. One reason for this is that a single client's effects on performance of the cluster are not capped, when the system is stressed, the system always runs slow regardless of how many customers are on the system since it is still running prioritized. Prioritization also makes it difficult for customer to understand the actual performance they are receiving, because prioritization does not extend an understandable idea to customers of the actual performance the customers are getting. Also, prioritization does not allow administrators to control how the system supports multiple customers and how the customers drive the system to load.